Priors_for_Learning_Outcome_Model
SM
2023-10-25
Forming Priors
Prior distributions for our model are set based on previous literature and inputs from experts. Experts’ inputs are obtained via focused group discussion and survey.
Stage 1: Priors from literature
The objectives of collecting prior information from literature:
- To identify variables that have direct association with the targeted outcome
- To identify the direction and degree of associations between the variables and the outcome
- To explore the changes in values of outcomes affected by different variables (when applicable)
Applicability and generalizability of data on our population
The applicability and generalizability of data are determined by the extent of similarity between the study population and our population.
Background info of our population
- Location- Yangon, Myanmar
- Population- Professional football players
- Gender- Male and Female
- Age- 15 to 30
- Education level- highschool to college level students, older players are university graduates
Intervention 1: Improving Nutritional Self-reliance
- Nutrition education (Nutrition Guide and a series of in-person
classes)
- Food groups (basic level)
- Types of nutrients (basic level)
- Healthy plate (basic level)
- Macronutrient and fluid requirements (Intermediate to advance level)
- Calculation of protein-energy/ fluid requirements (Advance level)
- Food exchange (Advance level)
Intervention 2: Guided Personalized Nutrition
- Nutrition education (a 3-hour in-person class)
- Food groups (basic level)
- Types of nutrients (basic level)
- Healthy plate (basic level)
- Macronutrient and fluid requirements (Intermediate level)
Collecting Priors from Literature Review
\(\color{brown}{\text{Study Population}}\)
Category
Location
Population
Age
Education level
Applicability
Data
Taiwan
College students, Acedamic staff
18 to 60
Current students to Phd
NA
Match
Low
Medium
Medium
Medium
Low to Medium
\(\color{brown}{\text{Association between Variables and Learning Outcome}}\)
Variable
Interest in learning (I)
Learning hours (T)
Teacher’s instructional attitude (Mo)
I*Mo
T*Mo
Direction and Degree of Association
Positive, Significant
Positive, Significant
Positive, Significant
Positive, Significantly strong
Positive, Significantly strong
Path Coefficient Value
0.462
0.451
0.442
0.691
0.672
When a teacher’s instructional attitude exerts a positive extraneous effect, H1, H2 and H3 appear relatively insignificant, compared with the increased significance of H4 and H5 statistically.
\(\color{brown}{\text{Study Population}}\)
Category
Location
Population
Age
Education level
Applicability
Data
Indonesia
High school student
16 to 17
Grade 11
NA
Match
Medium
Medium
Medium
Medium
Medium
\(\color{brown}{\text{ Association between Variables and Learning Outcome }}\)
Variable
Teacher’s communication skills (CS)
Student’s motivation to learn (LM)
CS*LM
Direction and Degree of Association
Positive, Significant
Positive, Significant
Positive, Significant
R-square Value
NA
NA
0.216
\(\color{brown}{\text{Changes in Value of Outcome}}\)
Every 1 point increase in communication will be followed by an increase in learning outcomes of 0.155 and every 1 point increase in learning motivation will be followed by an increase in learning outcomes of 0.108.
Communication skills and learning motivation contribute to the value of student learning outcomes by 21.60%, while the remaining 78.40% is contributed by other factors not examined in this study. Other variables that were not examined were internal factors (health, intelligence, interests) and external factors (family and community environment).
\(\color{brown}{\text{Study Population}}\)
Category
Location
Population
Age
Education level
Applicability
Data
Indonesia
High school student
16 to 17
Grade 11
NA
Match
Medium
Medium
Medium
Medium
Medium
\(\color{brown}{\text{ Association between Variables and Learning Outcome }}\)
Variable
Motivation (M) (self/external)
Habit (H)
M*H
Direction and Degree of Association
Positive, Significant, Weak
Positive, Significant, Weak
Positive, Significant, Weak
R-square Value
0.217
0.235
0.302
\(\color{brown}{\text{Study Population}}\)
Category
Location
Population
Age
Education level
Applicability
Data
Indonesia
High school student
16 to 17
Grade 11
NA
Match
Medium
Medium
Medium
Medium
Medium
\(\color{brown}{\text{ Association between Variables and Learning Outcome }}\)
Variable
Creativity (X1)
Interest in Learning (X2)
X1*X2
Direction and Degree of Association
Positive, Significant
Positive, Significant
Positive, Significant, Strong
R-square Value
NA
NA
0.503
\(\color{brown}{\text{Changes in Value of Outcome}}\)
Student’s creativity, interest, and creativity and interest have an effect of 14%, 41.8% and 50.3% on student achievement in economics subjects for class XI Social Sciences SMA Ekasakti Padang, the remaining 49.7% is influenced by several other factors.
\(\color{green}{\text{Generate Initial Model}}\)
We chose 4 papers as reference for our initial priors. Our search focused on the papers that studied variables with potential impact on learning outcome in a traditional classroom setting. Intervention studies (novel teaching method, learning environment, hybrid classroom, etc) were excluded.
None of the selected studies has a population closely matched (high applicability) to our target population. Hence, the papers’ findings cannot be applied directly to our model, but they will be useful in building the basic framework of the model. Paper 1, 2, 3 and 4 quantified the relationship between variables (Changes in the Value of Outcome), which could be very useful in coding of our model. Unfortunately due to differences in population and study subject, we were not able to use those results.
Thus, we summarized the results- usable for our model- of the four papers as follows:
- Student’s interest in learning, teacher’s attitude and learning hour can improve learning outcome, but if all three exist together (teacher’s attitude being significant factor), the impact on learning outcome improves significantly. (beta approx 0.4 to 0.6)
- Teacher’s communication skills and student’s motivation to learn- particularly if both are present- can improve learning outcome. (explain 21.6% of variation)
- Student’s motivation and study habit- particularly when coexist- can improve learning outcome (explain 30.2% of variation)
- Student’s creativity and interest in learning- particularly when coexist- can improve learning outcome (explain 50.3% of variation)
- Among Indonesian high school students in Padang, internal factors (health, intelligence, etc) and external factors (family and community environment, etc) may also affect their learning outcome. (We need to identify variables- not studied in the literature- with potential effect on learning outcome for our population)
\(\color{green}{\text{The Initial Model based on Literature}}\)
\(\color{green}{\text{Questions for Stage 2: Model Building}}\)
- What are the core variables for learning outcome for our population?
- What are the percent contributions of core variables to the outcome?
Stage 2: Model Building
A conceptual model was drafted during focus group discussions with football players, coaches, cook/chef, sports scientist, medical and management staff. The conceptual model was drafted in three stages.
- Stage 1: A model for learning outcome
- Stage 2: A model for improved diet given the learning outcome
- Stage 3: A model for improved sports performance given the total investment (cost) and improved diet
According to MFF management, the main goal or outcome of the intervention was to increase chances of winning the games. However, we need to consider if such outcome is achievable (measurable) with our intervention. To win a football match needs more than a good nutrition, and thus, good nutrition may not have a strong causal effect on “increased chance of winning a game.” Hence, we set the outcomes of our intervention as follows:
Note: The intervention for “Food quality and safety at kitchens” was already done during the 2-month internship.
This document focuses on the first outcome of our multistage model “the learning outcome”- improved nutritional knowledge and practice (eating habit). To achieve the second outcome “improved diet,” the MFF football players need to be provided with the right food in ample amount by the kitchens, on top of having good nutrition knowledge and eating habits. Hence, we did the food service intervention (Food quality and safety at kitchens) first. The conditions of food service after the intervention and chances of quality maintenance were considered in our model.
\(\color{red}{\text{Focus Group Discussion}}\)
The focus group discussion for the first outcome was done with eight players from four teams- three men teams and one women team. They were grouped into two groups- one group for Intervention 1 and another for Intervention 2.
We explained in detail about the two interventions and provided some questions to spark the thinking process, before the groups were asked to draft model.
Two main questions were
What are the main contributing factors to meet each objective of the nutrition training?
(What do you need to learn and understand (apply) each lesson? e.g. visual aid, practice session)
What can hinder or support the main contributing factors?
(What can interfere with your learning? e.g. lack of energy after training)
\(\color{red}{\text{Differences in Learning Outcome between Interventions}}\)
The learning outcome was achieved 100 percent if all objectives of nutrition training were met.
Objectives of nutrition training for Intervention 1 (Nutritional self-reliance):
- Know the basic food groups (10%)
- Know the type of nutrients and their food sources (15%)
- Know parts of a healthy plate (15%)
- Know the macronutrient and fluid requirements for football players (20%)
- Know how to calculate of protein-energy/ fluid requirements (20%)
- Know how to do simple meal planning using food exchange list (20%)
Objective of nutrition training for Intervention 2 (Guided personalized nutrition):
- Know the basic food groups (25%)
- Know the type of nutrients and their food sources (25%)
- Know parts of a healthy plate (25%)
- Know the macronutrient and fluid requirements for football players (25%)
\(\color{red}{\text{1-2 Cafe Approach}}\)
The players were first asked to list their answers to the questions (encouraged to add more points as needed) individually, and then discussed with their group members to create a new list. Based on the lists, model drafts were drawn by the two groups.
The groups presented their model, followed by an open discussion where each group provided additional inputs and suggestions for the other group. We collected the model drafts for intervention 1 and 2 after both groups approved the models. We then provided calibration training to the participants.
A survey questionnaire was developed based on the variables from the draft models and literature review model. A copy of questionnaire was given to the team captain of each team. The captain was asked to bring the questionnaire back to the team and fill in the estimates (lower and upper ranges) together with their team members. The forms were collected after a week.
Since we needed inputs from the players for all three models, we developed the questionnaire after drafting all models. Eight new players were requested for each modelling exercise. Thus, a total of 24 players (6 players from each team) were given calibration training after drafting the third and final model. The whole team- with the help of players trained in proper calibration- filled out the estimates for variables in survey questionnaire. After collecting all survey forms, we confirmed the core variables and drew the final multistage model based on the drafts.
\(\color{red}{\text{Model Drafts for Learning Outcome}}\)
Eight football players drafted the preliminary models for learning outcome.
\(\color{brown}{\text{ Model Draft for Learning Outcome (Intervention 1)}}\)
\(\color{brown}{\text{ Model Draft for Learning Outcome (Intervention 2)}}\)
Based on the two drafts, we designed our interventions.
Intervention 1: Nutritional Self-reliance
- 1-hour class twice per week for 2 months (total 16 hours)
- 6 hours of theory
- 10 hours of practical (calculation, food exchange, practice with real food)
- Agreement with coach to reduce training hours on class day (schedule away from training)
Intervention 2: Guided Personalized Nutrition
- 1-hour class once a week for 3 weeks (total 3 hours)
- Agreement with coach to reduce training hours on class day (schedule away from training)
\(\color{red}{\text{Survey}}\)
This was the last stage of “Priors for Learning Outcome.” We developed a survey form to assess the attitude, behavior and current nutrition knowledge of MFF players. The survey contained 20 questions that covered all three models.
As mentioned above, the form was given to the team captain after drafting all models, and the whole team would answer the survey together. We could use this approach because our population was small and homogeneous. The survey would allow us to estimate better ranges for input variables of our models.